Adaptive tracking control algorithm for flexible power point of photovoltaic system considering dynamic environment
CSTR:
Author:
Clc Number:

TM615

  • Article
  • | |
  • Metrics
  • |
  • Reference [16]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    A major problem related to the growing popularity of grid connected photovoltaic power generation is the operational challenges (such as overload and overvoltage) due to the variability of photovoltaic power generation. Flexible power point tracking (FPPT) can limit the photovoltaic output power to a specific value to solve some integration problems. The traditional FPPT algorithm based on disturbance observation has the problem of slow dynamics. Therefore, an adaptive FPPT algorithm is proposed in this paper. The proposed algorithm has fast dynamic characteristics under the quick changing environment conditions (such as cloud layer passing), while maintaining low power oscillation in the steady state. The proposed algorithm uses additional measurement samples under each disturbance to observe changes in operating conditions (such as solar irradiance). Then, the voltage step is calculated adaptively according to the observation conditions (such as transient or steady state) to improve the tracking performance. Finally, the simulation experiment on a 3 kVA single-phase photovoltaic grid connected system verifies the effectiveness of the algorithm in terms of fast dynamics and high accuracy under different operating conditions.

    Reference
    [1] Gupta A, Chauhan Y K, Pachauri R K. A comparative investigation of maximum power point tracking methods for solar PV system[J]. Solar Energy, 2016, 136:236-253.
    [2] 刘云, 应康, 辛焕海, 等. 基于二次插值法的光伏发电系统控制策略[J]. 电力系统自动化, 2012, 36(21):29-35.Liu Y, Ying K, Xin H H, et al. A control strategy for photovoltaic generation system based on quadratic interpolation method[J]. Automation of Electric Power Systems, 2012, 36(21):29-35. (in Chinese)
    [3] Sangwongwanich A, Yang Y H, Blaabjerg F. A sensorless power reserve control strategy for two-stage grid-connected PV systems[J]. IEEE Transactions on Power Electronics, 2017, 32(11):8559-8569.
    [4] 张露江, 张利, 杨要伟, 等. 基于改进贝叶斯网络的风机齿轮箱自动诊断策略研究[J]. 电力系统保护与控制, 2019, 47(19):145-151.Zhang L J, Zhang L, Yang Y W, et al. Research on automatic diagnosis strategy of wind turbine gearbox based on improved Bayesian network[J]. Power System Protection and Control, 2019, 47(19):145-151. (in Chinese)
    [5] 倪雨, 郝帅翔. 扰动观测法控制MPPT系统运动特性分析[J]. 电子学报, 2015, 43(7):1388-1394.Ni Y, Hao S X. Motion characteristics analysis of P & Q control MPPT system[J]. Acta Electronica Sinica, 2015, 43(7):1388-1394. (in Chinese)
    [6] 高嵩, 罗浩, 何宁, 等. 基于MPPT的新型变步长增量电导法的研究[J]. 电气传动, 2015, 45(2):16-19, 49.Gao S, Luo H, He N, et al. Research on a new method for variable step size INC based on maximum power point tracking[J]. Electric Drive, 2015, 45(2):16-19, 49. (in Chinese)
    [7] 赵亮, 刘友波, 余莉娜, 等. 基于深度信念网络的光伏电站短期发电量预测[J]. 电力系统保护与控制, 2019, 47(18):11-19.Zhao L, Liu Y B, Yu L N, et al. Short-term power generation forecast of PV power station based on deep belief network[J]. Power System Protection and Control, 2019, 47(18):11-19. (in Chinese)
    [8] 朱梓嘉, 肖辉, 赵帅旗, 等. 基于并行组合进化算法的光伏阵列最大功率点追踪[J]. 电力系统保护与控制, 2020, 48(4):1-10.Zhu Z J, Xiao H, Zhao S Q, et al. Maximum power point tracking of photovoltaic array based on parallel combination evolutionary algorithm[J]. Power System Protection and Control, 2020, 48(4):1-10. (in Chinese)
    [9] 潘明明, 孙晓辉, 于建成. 基于改进Kalman滤波块状态估计方法的分布式光伏发电预测[J]. 供用电, 2019, 36(2):56-60.Pan M M, Sun X H, Yu J C. A distributed photovoltaic generation prediction based on improved kalman filter block state estimation method[J]. Distribution & Utilization, 2019, 36(2):56-60. (in Chinese)
    [10] Ghasemi M A, Foroushani H M, Parniani M. Partial shading detection and smooth maximum power point tracking of PV arrays under PSC[J]. IEEE Transactions on Power Electronics, 2016, 31(9):6281-6292.
    [11] Yang Y H, Blaabjerg F, Wang H. Constant power generation of photovoltaic systems considering the distributed grid capacity[C]//2014 IEEE Applied Power Electronics Conference and Exposition-APEC 2014, March 16-20, 2014, Fort Worth, TX, USA. IEEE, 2014.
    [12] Urtasun A, Sanchis P, Marroyo L. Limiting the power generated by a photovoltaic system[C]//10th International Multi-Conferences on Systems, Signals & Devices 2013(SSD13), March 18-21, 2013, Hammamet, Tunisia. IEEE, 2013.
    [13] Escobar G, Pettersson S, Ho C N M, et al. Multi-sampling maximum power point tracker (MS-MPPT) to compensate irradiance and temperature changes[J]. IEEE Transactions on Sustainable Energy, 2017, 8(3):1096-1105.
    [14] Tafti H D, Maswood A I, Konstantinou G, et al. A general constant power generation algorithm for photovoltaic systems[J]. IEEE Transactions on Power Electronics, 2018, 33(5):4088-4101.
    [15] Salman, Ai X, Wu Z Y. Design of a P-&-O algorithm based MPPT charge controller for a stand-alone 200W PV system[J]. Protection and Control of Modern Power Systems, 2018, 3:25.
    [16] Kollimalla S K, Mishra M K. A novel adaptive P&O MPPT algorithm considering sudden changes in the irradiance[J]. IEEE Transactions on Energy Conversion, 2014, 29(3):602-610.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

施永豪,董志诚.考虑动态环境下的光伏系统柔性功率点自适应跟踪控制算法[J].重庆大学学报,2021,44(8):59~75

Copy
Share
Article Metrics
  • Abstract:493
  • PDF: 947
  • HTML: 1159
  • Cited by: 0
History
  • Received:March 20,2020
  • Online: August 31,2021
Article QR Code